03129cam a2200361 i 4500 22444577 Ost 20260410175043.0 260106s2022 nyuad frb 001 0 eng 2022009851 9781462549863 DLC eng rda DLC DLC clrauoh pcc 300.15195 Enders, Craig K., author. Applied missing data analysis / Craig K. Enders. Second edition. New York : The Guilford Press, 2022 xiv, 546 pages : illustrations. text txt rdacontent unmediated n rdamedia volume nc rdacarrier Methodology in the social sciences Revised edition of the author's Applied missing data analysis, 2010. Includes bibliographical references (pages 493-517) and index. Introduction to missing data -- Maximum likelihood estimation -- Maximum likelihood estimation with missing data -- Bayesian estimation -- Bayesian estimation with missing data -- Bayesian estimation for categorical variables -- Multiple imputation -- Multilevel missing data -- Missing not at random processes -- Special topics and applications -- Wrap-up. "The most user-friendly and authoritative resource on missing data has been completely revised to make room for the latest developments that make handling missing data more effective. The second edition includes new methods based on factored regressions, newer model-based imputation strategies, and innovations in Bayesian analysis. State-of-the-art technical literature on missing data is translated into accessible guidelines for applied researchers and graduate students. The second edition takes an even, three-pronged approach to maximum likelihood estimation (MLE), Bayesian estimation as an alternative to MLE, and multiple imputation. Consistently organized chapters explain the rationale and procedural details for each technique and illustrate the analyses with engaging worked-through examples on such topics as young adult smoking, employee turnover, and chronic pain. The companion website includes datasets and analysis examples from the book, up-to-date software information, and other resources. Subject areas/Key words: advanced quantitative methods, management, survey, longitudinal, structural equation modeling, handling, how to handle, incomplete, multivariate, social research, behavioral sciences, statistical techniques, textbooks, seminars, doctoral courses, multiple imputation, models, MCAR, MNAR, Bayesian Audience: Researchers and graduate students in psychology, education, management, family studies, public health, sociology, and political science"-- Provided by publisher. Social sciences Statistical methods. Missing observations (Statistics) Social sciences Research Methodology. https://itmsp.museknowledge.com/UOH?qurl=https://libros-uoh.uoh.cl/ebook_2/Applied-missing-data-analysis VER LIBRO DIGITAL ddc BOOK 0 6873 6873 2026-03-12 00:00:00 35672010609 0 300.15195 E565a 2022 35672010609 1 2026-01-06 BOOK 0 ddc 0 0 COL_GRAL 0 BCENTRAL BCENTRAL 2025-11-19 126380.00 2026-03-12 00:00:00 35672010610 0 300.15195 E565a 2022 35672010610 2 2026-01-06 BOOK 0 ddc 0 0 COL_GRAL 0 BCENTRAL BCENTRAL 2025-11-19 126380.00 2026-03-12 00:00:00 35672010611 0 300.15195 E565a 2022 35672010611 3 2026-01-06 BOOK 0 ddc 0 0 COL_GRAL 0 BCENTRAL BCENTRAL 2025-11-19 126380.00